Importance sampling is a potentially powerful technique for e ciently estimating the probabilities of rare events in discrete event systems. The work presented here makes three contributions to importance sampling research. First, a convenient mechanism for specifying complex importance sampling heuristics is presented. Second, a method for applying importance sampling to stochastic activity ne...

This paper investigates the network location problem for single-server facilities that are subject to congestion. In each network edge, customers are uniformly distributed along the edge and their requests for service are assumed to be generated according to a Poisson process. A number of facilities are to be selected from a number of candidate sites and a single server is located at each facil...

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusion Search, SDS, a nondeterministic search algorithm able to rapidly lo...

considering the network structure is one of the new approaches in studying stochastic pert networks (spn). in this paper, planar networks are studied as a special class of networks. two structural reducible mechanisms titled arc contraction and deletion are developed to convert any planar network to a series-parallel network structure. in series-parallel spn, the completion time distribution fu...